Users: BYOAs – Be Your Own Analysts!
First, the changes. Private investment firm Alta Communications, already majority owners of pioneering IT analyst firm Yankee Group, is investing another $10 million in Yankee. Yankee's also moving its current CEO and President Emily Nagle Green to the position of board chair and looking for a new CEO. The company is also focusing almost exclusively on the concept of the "anywhere network" Green used to re-launch Yankee when she joined the company in 2005. Global connectivity is important to many vendors and larger users, but far beyond the more immediate and tactical concerns of many business decision-makers, especially those at smaller companies.
Separately, Gartner's bought up AMR Research, a respected firm focused largely on supply chain issues. IDC remains independent, but also largely focused on sizing IT markets. So as far as business-focused IT users are concerned, Forrester and Gartner are basically the only games in town in terms of breadth of coverage, depth of coverage and sufficient time in the game.
And some pretty highly respected individual analysts are going to work for IT vendors. Recent examples include Andi Mann, who's departed Enterprise Management Associates for CA, and Gordon Haff, who's leaving Illuminata for Red Hat. Such moves may make the vendors smarter and more responsive, but those benefits are likely largely limited to those vendors' customers, prospects and partners.
All of this change raises anew frequently recurring questions about the roles played and value created by IT industry analysts, especially for cash-strapped, resource-constrained users. Vendors need analysts, internal and independent, to gain and maintain more accurate and complete views of the goals, needs and constraints shaping the behaviors of their customers and prospects.
But what about users, especially those from smaller companies without significant budgets to spend on services from traditional analyst firms? Can a logical argument be made for or against users relying upon those firms at all?
It seems that such an argument can be made, and that it can be made most effectively against such reliance. Further, that argument is based at least in part on rigorous mathematics, specifically something called "the law of great (or large) numbers."
Basically, that law goes something like this. The more often you repeat an act, the more the aggregate set of repetitions will mirror likely averages for such behaviors. A coin flipped 1,000 or 10,000 times will come up heads slightly closer to 50 percent of the time than a coin flipped only 10 or 100 times.
A similar argument can be extrapolated about the percentage of repetitions of a task. Absent large numbers of repetitions of a task, the higher a percentage of total repetitions one considers, the closer that sample will be to the statistically expected average. So if something has only happened, say, 100 times, a sample of 90 of those times would approach statistically average behavior more closely than a sample of 10 of those times. At the very least, the higher-percentage sample would provide a more comprehensive foundation for predicting and acting upon the repeated task.
We believe this is directly relevant to the relationship between IT users and IT industry analysis. Most good analysts have seen similar situations lots of times, either in real terms or as a percentage of the total number of times such situations have arisen. For example, an analyst may have seen dozens or hundreds of companies go through implementation of a particular technology, while that same analyst may have also seen a high percentage of events that have not happened as frequently.
However, it is highly unlikely that any analyst seen a higher number or percentage of the things that go on at your company than you and your fellow technology users, influencers and decision-makers. This makes you and your colleagues far more qualified to make decisions, pronouncements and projections about the evolution of technologies at your company than any analyst. It should also give you the confidence to do so, especially if you have access to credible historical information about events and results that extend beyond your personal tenure and/or specific department at your organization.
Research of publicly available information indicates that user enterprises spent some $6.7 billion on market research in 2005 and approximately $15 billion in 2008. Further, in 2009, Gartner had approximately $1.1 billion in revenues, approximately 70 percent of which was generated by approximately 7,000 user companies. This results in an average annual expenditure of $110,000 per user company on Gartner services alone.
